Difference between revisions of "Manuals/calci/EXPONDIST"

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:<math> =0  ,  x<0</math>
 
:<math> =0  ,  x<0</math>
 
or   
 
or   
:<math>f(x;λ)= λe^-λ x .H(x)</math>
+
:<math>f(x;\lambda)= λe^{-\lambda x} .H(x)</math>
  
 
*where λ is the rate parameter and H(x) is the  Heaviside step function
 
*where λ is the rate parameter and H(x) is the  Heaviside step function
 
*This function is valid only on the interval [0,infinity).
 
*This function is valid only on the interval [0,infinity).
The cumulative distribution function is :F(x,λ)={1-e^-λ x,  x>=0
+
The cumulative distribution function is :<maths>F(x,\lambda)={1-e^{-\lambda x},  x\ge0</maths>
                                      <math>0    ,  x<0 </math>
+
                                        <math>0    ,  x<0 </math>
  or                                    :F(x,λ)=1-e^-λ x.H(x).  
+
  or                                    :F(x,λ)=1-e^{-\lambda x}.H(x).  
  
*The mean or expected value of the exponential distribution is: E[x]=1/ λ.
+
*The mean or expected value of the exponential distribution is: <math>E[x]=\frac{1}{ λ}</math>
*The variance of the exponential distribution is:Var[x]=1/ λ^2.
+
*The variance of the exponential distribution is: <math>Var[x]=\frac{1}{\lambda^2}</math>.

Revision as of 01:21, 29 November 2013

EXPONDIST(x,Lambda,cum)


  • is the value of the function
  • is the value of the rate parameter
  • is the logical value like TRUE or FALSE

Description

  • This function gives the exponential distribution. This distribution used to model the time until something happens in the process.
  • This describes the time between events in a Poisson process i.e, a process in which events occur continuously and independently at a constant average rate.
  • For e.g Time between successive vehicles arrivals at a workshop.
  • In EXPONDIST(x, lambda,cu), xis the value of the function, lambda is called rate parameter and cu(cumulative) is the TRUE or FALSE. *This function will give the cumulative distribution function , when cu is TRUE,otherwise it will give the probability density function , when cu is FALSE.
  • Suppose we are not giving the cu value, by default it will consider the cu value is FALSE.
  • This function will give the error result when
1.  or  is non-numeric.
2.  or 

The probability density function of an exponential distribution is:

or

Failed to parse (syntax error): {\displaystyle f(x;\lambda)= λe^{-\lambda x} .H(x)}
  • where λ is the rate parameter and H(x) is the Heaviside step function
  • This function is valid only on the interval [0,infinity).

The cumulative distribution function is :<maths>F(x,\lambda)={1-e^{-\lambda x}, x\ge0</maths>

                                        
or                                     :F(x,λ)=1-e^{-\lambda x}.H(x). 
  • The mean or expected value of the exponential distribution is: Failed to parse (syntax error): {\displaystyle E[x]=\frac{1}{ λ}}
  • The variance of the exponential distribution is: .